Field cognition style is one of the most prominent areas of research within the broader field of cognition styles, where users with different field cognition styles exhibit distinct cognition preferences. To cater to both field-dependent and field-independent cognition style users, the work aims to construct a user experience evaluation system of information interaction design, providing cognitive theoretical foundations and methodological references for inclusive design. Firstly, the characteristics of various field cognition styles and information interaction design elements were systematically reviewed and subsequently questionnaires were used to identify user experience evaluation factors closely associated with these cognition styles. Secondly, the Goal-Question-Metric (GQM) paradigm was introduced to establish a user experience evaluation system tailored to different field cognition styles. Finally, the Analytic Hierarchy Process (AHP) was employed to calculate the weights of each evaluation indicator, and the feasibility of the evaluation system was discussed. In terms of evaluation indicators, the user experience evaluation system for different field cognition styles encompassed three objectives of the information layer, interaction layer and sensorial layer, with varying evaluation preferences among different cognition style groups. Field-dependent users tended to prefer products and scenarios that offered concise information, clear and fixed interaction modes, and conformed to their cognitive experiences. In contrast, field-independent users were more suited to products and scenarios characterized by rich information, free and personalized interaction modes, and elements that provided cognitive challenges. For information interaction products designed for diverse functions and scenarios, measuring cognition styles can directly and effectively define user needs and behavioral characteristics in information interaction design, which can potentially serve as a vital indicator within user personas, enriching the granularity of user profiling and accelerating the user research process.